Under weak grid conditions, the static var generator controlled by a virtual synchronous generator exhibits enhanced stability and can mitigate mid-frequency resonance in doubly-fed induction generator wind farms, which commonly occurs under grid-following control. To comparatively analyze the characteristics and mechanisms of the static var generator in improving resonance stability under single-loop and dual-loop virtual synchronous generator control modes, this study first establishes sequential impedance models for the static var generator and doubly-fed induction generator under different control modes. Subsequently, the impedance analysis method is employed to investigate the generation mechanism and key influencing factors of mid-frequency resonance. Furthermore, the dynamic performance and resonance suppression effectiveness of the static var generator under the virtual synchronous generator single-loop and dual-loop control modes are compared. Finally, simulation verification is conducted using the StarSim-HIL platform. The impedance analysis reveals that the grid-following static var generator introduces a negative damping region in the mid-frequency band, causing the system resonance. In contrast, the virtual synchronous generator control effectively reshapes the static var generator output impedance, elevating the phase from negative to positive damping in the critical frequency range, thereby fundamentally suppressing the resonance. And the dual-loop virtual synchronous generator control the static var generator, leveraging its current inner loop, exhibits superior reactive power tracking capability, faster and smoother transient responses, and enhanced rapidity and effectiveness in suppressing mid-frequency resonance.

As the grid-connection voltage level of the cascaded H-bridge (CHB) STATCOM increases, the number of cascaded cells also increases, and the switch fault leads to a higher risk of STATCOM operation. For instance, the open-circuit (OC) switch fault will deteriorate the power quality of the STATCOM output current. Therefore, the high efficiency and precision of OC switch fault localization are an assurance of STATCOM operation safety. Using the actual output voltage acquired from the AC voltage sensor installed at the output side of the CHB STATCOM, the fault characteristic of the voltage is obtained through comparison with the expected output voltage of the CHB STATCOM, and then combined with the mapping relationship of the switch trigger signals, a novel OC switch fault localization method based on timing logic is proposed. The proposed method, while ensuring rapid localization, eliminates the misjudgment caused by traditional methods and is not limited by the number of cells and faulty switches. Finally, the effectiveness of this method in the application of CHB STATCOM was verified through simulation and experiments.

For single-phase grid-forming enhanced CHB (GFM-ECHB) convertors, an increase in output active power and inductive reactive power leads to a higher modulation ratio, resulting in the degradation of grid-connection current. Although traditional harmonic suppression strategies can address similar issues, this article shows that they also affect the control stability of GFM-ECHB via small-signal perturbation modeling and pole distribution analysis. Moreover, this effect cannot be mitigated through independent power regulation of SMs. To address this issue, an optimized third-order harmonic injection (OTOI) strategy is proposed. It involves injecting third harmonics into each SM using an interleaved harmonic voltage injection method, while simultaneously employing a harmonic current suppression strategy to eliminate third harmonics, which a single-phase topology can’t naturally cancel. Ultimately, without reducing power output, all SMs remain undermodulated, effectively suppressing the third-harmonic component of the output current. Both simulation and hardware experiments validated the effectiveness of OTOI.

Existing research frequently attributes the frequent occurrence of resonances to three main factors: improper settings of internal control parameters in converters, the capacitive effect of collection cables, and the capacitive nature of some equipment's impedance characteristics within specific frequency bands. However, the fundamental causes and influencing factors behind high-frequency resonance in parallel systems comprising a Static Var Generator (SVG) and clustered Doubly-Fed Induction Generators (DFIG) have not been thoroughly investigated. Therefore, this study employs the harmonic linearization method to establish sequence impedance models for both the SVG and the clustered DFIGs. Using impedance analysis combined with stability criteria, the mechanism by which the energization of unload lines high-frequency resonance in the wind farm system is revealed. We specifically analyzed the impact of the number of wind turbines in operation, and variations in wind speed on the overall impedance of the wind farm system. Finally, electromagnetic transient simulations validated the correctness of the theoretical analysis concerning the resonance's nature and its triggering factors.

To address issues such as low conversion efficiency and low DC current stabilization accuracy in electrolytic rectification, a rectification scheme featuring coordinated control of the rectifier transformer and thyristors is proposed. The front stage adopts 18-step coarse adjustment via the rectifier transformer, while the rear stage employs fine adjustment using thyristors, thereby improving the system's power factor. First, the operational characteristics of the main circuit topology are analyzed. The analysis reveals that thyristor rectification constitutes a large time-delay system, which suffers from problems such as poor dynamic response and weak anti-interference capability. To tackle this, fractional-order theory is introduced and combined with conventional PI control, enabling more flexible control of the controlled object. Subsequently, to enhance the system's adaptability, a strategy integrating the frequency-domain graphical parameter tuning method with fuzzy adaptive fractional-order PI control is proposed. Simulation and experimental results demonstrate that the proposed strategy exhibits excellent dynamic and static performance as well as robustness.

Wind power prediction plays a crucial role in enhancing power grid stability and wind energy utilization efficiency. Existing prediction methods demonstrate insufficient integration of multi-variate features, such as wind speed, temperature, and humidity, along with inadequate extraction of correlations between variables. This paper proposes a novel multi-variate multi-scale wind power prediction method named multi-scale variational mode decomposition informer (MSVMD-Informer). First, a multi-scale modal decomposition module is designed to decompose univariate time-series features into multiple scales. Adaptive graph convolution is applied to extract correlations between scales, while self-attention mechanisms are utilized to capture temporal dependencies within the same scale. Subsequently, a multi-variate feature fusion module is proposed to better account for inter-variable correlations. Finally, the informer is reconstructed by integrating the aforementioned modules, enabling multi-variate multi-scale wind power forecasting. The proposed method was evaluated through comparative experiments and ablation studies against seven baselines using a public dataset and two private datasets. Experimental results demonstrate that our proposed method achieves optimal metric performance, with its lowest MAPE scores being 1.325%, 1.500% and 1.450%, respectively.

As a new dynamic reactive power compensator, the grid-forming Static Var Generator (GF-SVG) can not only provide reactive power-voltage support, but also has inertial support capability. It has been experimentally deployed in many wind farms. However, studies have shown that when the three-phase short-circuit fault occurs in the wind farm, the transient overcurrent during the fault occurrence and fault clearance is suppressed, making it difficult for GF-SVG to use traditional fixed virtual impedance. Aiming at the problem, firstly, the influence of virtual reactance on control stability is analyzed using the GF-SVG’s current open-loop transfer function. Secondly, based on the existing current limitation strategies of GF-SVG, an adaptive virtual reactance current limitation strategy suitable for symmetrical faults of the power grid is proposed, which limits GF-SVG’s transient overcurrent during fault occurrence and fault clearance stage to the tolerance range of GF-SVG’s power devices. Based on the GF-SVG’s active power loop and reactive power loop small signal models, the availability of the proposed adaptive virtual reactance in suppressing the DC voltage drop of GF-SVG is analyzed, and shortening the transient overvoltage recovery time of the wind farm after the fault clearance is also discussed. Finally, electromagnetic simulation proves the effectiveness and correctness of the proposed adaptive current limitation method.

Complex power electronic topologies, such as modular multilevel converter (MMC), frequently experience broadband oscillation. To reveal the theoretical mechanism, this article models MMC based on linear-time-periodic-variable (LTPV) approach and obtains analytical expression of its ac-side admittance explicitly, formulated as a six-degree polynomial fraction. Three intrinsic oscillation modes of MMC topology are then estimated, and Foster-type circuit corresponding to the impedance is synthesized, revealing the root cause of multiple oscillation modes. It is found that due to the existence of arm capacitors, MMC impedance presents multiple LC oscillations. Increasing the capacitance can mitigate the oscillation, making the output impedance close to the filter inductor of two-level converter. The derivation and analysis are extended to single-loop grid-forming control, current control, and multiple-loop control. Correctness of the impedance model and oscillation frequency estimation is verified through impedance measurement and hardware-in-the-loop test.

In Doubly Fed Induction Generator (DFIG)-based wind farms with Static Var Generators (SVGs), high-frequency resonance will be more like to occur when an unloaded cable is put into operation, which will threaten the stable operation of the wind farm. To address this issue, the influence of power outer loops on the impedance of grid-connected inverters is considered. Based on harmonic linearization, theoretical models for the sequence impedances of DFIGs, Grid-following (GFL) SVGs, and Grid-forming (GFM) SVGs are established. The correctness of the three models is verified by impedance scanning using the frequency sweep method. Through a comparative analysis of these sequence impedances, it is found that unlike the GFM SVG (which exhibits inductive impedance), the GFL SVG exhibits capacitive impedance in the high-frequency band, which leads to negative damping characteristics in the high-frequency band for the wind farm system with the grid-following SVG; thereby, the risk of high-frequency resonance also increases accordingly. On the contrary, GFM control adopted by SVGs can effectively eliminate the negative damping region in the high-frequency band for wind farms to suppress high-frequency resonance. Meanwhile, for grid-forming SVGs, the parameter variations in power synchronous loops have no significant impact on the suppressing effect of high-frequency resonance for wind farms. Finally, an electromagnetic simulation model for a DFIG-based wind farm system with an SVG is established using the StarSim-HIL (hardware-in-the-loop) experiment platform, and the simulation results validate the correctness of the theoretical analysis.

In order to achieve the stable dc voltage support during the process of reactive power compensation, the cells within the chain of CHB STATCOM are equipped with high-capacity capacitors (along with dc voltage detection devices). However, over time, these capacitors exhibit varying degrees of aging, leading to discrepancies in capacitance reduction or variations in the equivalent series resistance (ESR) values, which not only complicates the task of balancing the capacitor voltages across the chain’s cells, but also increases the risk of device overvoltage. To address the problem, an online monitoring method for capacitor conditions based on sensorless capacitor voltage detection is proposed. Initially, the mapping relationship between the capacitance and its corresponding voltages is established on basis of the cell’s switching state and the principle of energy conservation. Subsequently, the capacitance estimation algorithm is constructed based on the data from sensorless capacitor voltage detection. In addition, the factors contributing to capacitance estimation errors are analyzed, and potential solutions are offered. This method facilitates the detection of each cell’s dc voltage and capacitance variations, while eliminating additional costs related to dc sensors and its associated communication devices. Ultimately, the effectiveness of the proposed online monitoring method is verified by MatLab/Simulink simulation and the StarSim experimental platform.

With the expansion of wind power clusters in power system, medium and high frequency oscillations in wind farm area are preliminarily emerging. At present, linear analysis such as impedance analysis are mainly used to analyse the grid-connected oscillation of renewable energy generation. However, the explanation of the oscillation mechanism is not intuitive and does not take into account the nonlinearity of converter. Considering the influence of external loop control of SVG and direct-drive wind turbine on the medium-frequency characteristics of the parallel system, a reduced-order nonlinear model under voltage time scale is established. The conjoint analysis of Jacobi matrix, bifurcation diagram and phase space trajectory are applied to study the influence rule of machine-side output power and short-circuit ratio on the oscillation behaviour of the parallel system. In addition, the oscillation evolution process is analysed from the dynamic standpoint. It is found that the system operates on the limit-loop state when the medium-frequency oscillation occurs, which reveals the mapping relationship between the oscillation amplitude and the limit-loop trajectory. The experimental results ultimately validate the theoretical analysis conducted on the StarSim-HIL (hardware-in-the-loop) experiment platform.

This paper proposed a model predictive control(MPC)secondary frequency control method considering wind and solar power generation stochastics.The extended state-space matrix including unknown stochastic power disturbance is established,and a Kalman filter is used to observe the unknown disturbance.The maximum available power of wind and solar DGs is estimated for establishing real-time variable constraints that prevent DGs output power from exceeding the limits.Through setting proper weight coefficients,wind and photovoltaic DGs are given priority to participate in secondary frequency control.The distributed restorative power of each DG is obtained by solving the quadratic programming(QP)optimal problem with variable constraints.Finally,a microgrid simulation model including multiple PV and wind DGs is built and performed in various scenarios compared to the traditional secondary frequency control method.The simulation results validated that the proposed method can enhance the frequency recovery speed and reduce the frequency deviation,especially in severe photovoltaic and wind fluctuations scenarios.

Modular multilevel converter (MMC) has complex topology, control architecture and broadband harmonic spectrum. For this, linear-time-periodic (LTP) theory, covering multi-harmonic coupling relations, has been adopted for MMC impedance modeling recently. However, the existing MMC impedance models usually lack explicit expressions and general modeling procedure for different control strategies. To this end, this paper proposes a general impedance modeling procedure applicable to various power converters with grid-forming and grid-following control strategies. The modeling is based on a unified representation of MMC circuit as the input and output relation between the voltage or current on the AC side and the exerted modulation index, while the control part vice versa, thereby interconnected as closed-loop feedback. With each part expressed as transfer functions, the final impedance model keeps the explicit form of harmonic transfer function matrix, making it convenient to directly observe and analyze the influence of each part individually. Thereby the submodule capacitance is found as the main cause of difference between MMC impedance compared to two-level converter, which will get closer as the capacitance increases. Effectiveness and generality of the impedance modeling method is demonstrated through comprehensive comparison with impedance scanning using electromagnetic transient simulation.

Frequency-domain impedance or admittance model is widely applied to analyze the harmonic stability of power electronic converters. Conventionally, the converter impedance is modeled holistically, without exhibiting the sole effect of different control and phase-locked loop (PLL). Besides, harmonic voltage or current injection external to the converter is usually adopted, which involves dedicated equipment and introduces unexpected inner impedance. In this article, the response of voltage perturbation upon ac–dc power converters along various voltage signal flow paths is analyzed, based on the superposition principle. Each part of admittance and its effect on stability can therefore be quantified explicitly. By injecting harmonic perturbation through the identified paths within the converter controller, each part of the admittances, with and without the concerned control or PLL blocks, is measured and summed to be the total admittance. Harmonic voltage mitigation control implemented on a grid-forming converter creates an ideal grid with constant voltage and nearly zero inner impedance at the injected harmonic frequency. The proposed admittance analysis and measurement are successfully applied to the power converter with different PLL, voltage feedforward, output power control, dc voltage control, and grid-forming cascaded control. The effectiveness of the analysis and the proposed admittance measurement approach is validated by comprehensive simulation and hardware tests.

As the high penetration of wind and photovoltaic distributed generation (DG) in the microgrid, the stochastic and low inertia emerge, bringing more challenges especially when the microgrid operates in isolated islands. Nevertheless, the reserve power of DGs in deloading control mode can be utilized for frequency regulation and mitigating frequency excursion. This paper proposed a model predictive control (MPC) secondary frequency control method considering wind and solar power generation stochastics. The extended state-space matrix including unknown stochastic power disturbance is established, and a Kalman filter is used to observe the unknown disturbance. The maximum available power of wind and solar DGs is estimated for establishing real-time variable constraints that prevent DGs output power from exceeding the limits. Through setting proper weight coefficients, wind and photovoltaic DGs are given priority to participate in secondary frequency control. The distributed restorative power of each DG is obtained by solving the quadratic programming(QP) optimal problem with variable constraints. Finally, a microgrid simulation model including multiple PV and wind DGs is built and performed in various scenarios compared to the traditional secondary frequency control method. The simulation results validated that the proposed method can enhance the frequency recovery speed and reDGce the frequency deviation, especially in severe photovoltaic and wind fluctuations scenarios.

With the rapid growth of wind power penetration, wind farms (WFs) are required to implement frequency regulation that active power control to track a given power reference. Due to the wake interaction of the wind turbines (WTs), there is more than one solution to distributing power reference among the operating WTs, which can be exploited as an optimization problem for the second goal, such as fatigue load alleviation. In this paper, a closed-loop model predictive controller is developed that minimizes the wind farm tracking errors, the dynamical fatigue load, and the load equalization. The controller is evaluated in a medium-fidelity model. A 64 WTs simulation case study is used to demonstrate the control performance for different penalty factor settings. The results indicated the WF can alleviate dynamical fatigue load and have no significant impact on power tracking. However, the uneven load distribution in the wind turbine system poses challenges for maintenance. By adding a trade-off between the load equalization and dynamical fatigue load, the load differences between WTs are significantly reduced, while the dynamical fatigue load slightly increases when selecting a proper penalty factor.

The cascaded H-bridge (CHB) static synchronous compensator (STATCOM) has been widely used in wind farm and conflux station. As the grid-connected voltage increases, the number of CHB proportionately increases. In order to achieve the capacitor voltage balance, it is necessary to independently detect the capacitor voltage of all H-bridge cells, which raises the cost of capacitor voltage detection. To solve this problem, the mapping relationship is studied between the converter output voltage and capacitor voltages by analyzing carrier phase-shifted sinusoidal pulse width modulation technique, and special switching mode is first found. Based on the abovementioned finding, without changing the conventional CHB topology, an improved sensorless detection method is proposed to solve the problems of detection error, large computation burden, and the application limitation in existing sensorless detection methods. Compared with conventional sensor detection, this method not only saves dc voltage sensors and data transmission channels but also suppress the third harmonics in the converter current. Finally, the effectiveness of the detection method applied on CHB STATCOM is proved by simulation and experiment.

目前,对多能量虚拟电厂在多种不确定性条件下的优化调度问题研究存在不足.针对这些不确定性问题,提出计及激励型需求响应的热电互联虚拟电厂优化调度模型.首先,针对分布式能源发电的不确定性,根据不同时刻风速、光照强度相关性,利用Student-T Copula函数得到风光发电场景;其次,综合考虑电热相关约束,建立以虚拟电厂效益最大为目标函数的优化调度模型;然后,采用改进型多元宇宙算法对所提出的模型进行优化求解;最后,通过算例仿真,验证所提出的优化调度模型能够平缓负荷曲线,减少环境污染,提高虚拟电厂整体经济效益.

可再生能源出力及负荷需求的不确定性严重影响电热联合系统的鲁棒优化运行.基于此,提出了一种改进Wasserstein度量的考虑源-荷不确定性电热联合系统分布鲁棒优化调度模型.建立基于极端场景下改进Wasserstein度量的风电预测功率模糊集,缩减风电预测功率模糊集的规模,进而提出基于梯度归一化改进Wasserstein生成对抗网络方法对负荷需求的不确定性进行建模,提高负荷不确定性建模的精度;构建综合考虑发电成本、调节成本等的分布鲁棒优化调度模型,并基于对偶理论和拉格朗日乘子法将该模型转换成可求解的数学模型;以修改的9节点系统及IEEE 118节点系统为例验证了所提出的模型具有更高的求解效率以及更好的经济性和鲁棒性.

配电网并联STATCOM机间谐波交互作用可能导致其系统运行失稳,文中从链内子模块载波的相对位置出发,分析非特征次谐波产生的根本原因,通过归纳电容吞吐有功功率变化规律,研究了谐波环流与子模块电容电压失衡之间的交互影响机理,构建了子模块电容电压均衡优化控制方法,最后搭建电平STATCOM双机仿真模型进行验证,仿真结果证明了理论分析和控制方法的正确性.